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BackgroundIncreasing evidence emphasizes the potential relationship between diabetes and OAB (overactive bladder). However, large population epidemiology is still lacking.MethodsThis cross-sectional study included six cycle NHANES surveys, with a total of 23863 participants. Logistic regression models were constructed to analyze the association between diabetes mellitus, diabetes-related markers, and inflammatory biomarkers with OAB. Restricted cubic splines were used to analyze the non-linear associations. Mediating analysis was performed to test the effect of inflammatory biomarkers on the relationship between diabetes-related markers and OAB. Finally, machine learning models were applied to predict the relative importance and construct the best-fit model.ResultsDiabetes mellitus participants’ OAB prevalence increased by 77% compared with non-diabetes. As the quartiles of diabetes-related markers increased, the odds of OAB monotonically increased in three models (all p for trend < 0.001). Glycohemoglobin exhibited a linear association with OAB (p for nonlinearity > 0.05). White blood cells significantly mediated the associations between diabetes-related markers (glycohemoglobin, fasting glucose, and insulin) with OAB, and the proportions were 7.23%, 8.08%, and 17.74%, respectively (all p < 0.0001). Neutrophils partly mediated the correlation between (glycohemoglobin, fasting glucose, and insulin) and OAB at 6.58%, 9.64%, and 17.93%, respectively (all p < 0.0001). Machine learning of the XGBoost model constructs the best fit model, and XGBoost predicts glycohemoglobin is the most important indicator on OAB.ConclusionOur research revealed diabetes mellitus and diabetes-related markers were remarkably associated with OAB, and systemic inflammation was an important mediator of this association.

BackgroundCurrently, there is limited research on the specific relationship between N, N-diethyl-m-toluamide (DEET) exposure and the odds of kidney stones. We aimed to investigate the relationship between DEET exposure and the prevalence of kidney stones.MethodsWe included 7,567 qualified participants in our research from the 2007–2016 NHANES survey. We carried out three logistic regression models to explore the potential association between DEET exposure and the odds of kidney stones. Spline smoothing with generalized additive models (GAM) was utilized to assess the non-linear relationship and restricted cubic spline (RCS) curves was to determine the dose–response association. Multivariate regression models were used to conduct stratified analysis and sensitivity analysis.ResultsBaseline characteristics of study participants presented the distribution of covariables. Regression analysis revealed that the odds of kidney stones were positively associated with the main metabolites of 3-diethyl-carbamoyl benzoic acid (DCBA) (log2) (OR = 1.05, 95% CI 1.02 to 1.08). The fourth quartile of urine DCBA showed a greater risk of kidney stones in the fully adjusted model (OR = 1.36, 95% CI 1.08 to 1.72). Another DEET metabolite of N, N-diethyl-3-hydroxymethylbenzamide (DHMB) was used to confirm the accuracy and stability of the results. The spline smoothing curve represented two main DEET metabolites had similar no-linear relationships and a positive trend with kidney stones proportion. RCS implied that the incidence of kidney stones rose with increasing levels of DEET exposure. High-risk groups on kidney stones were exhibited by stratified analysis under DEET exposure.ConclusionOur study suggests that DEET exposure is positively associated with odds of kidney stones. Further investigation into the underlying processes of this association is required to guide the prevention and treatment of kidney stones.

The tumor immune microenvironment is an important prognostic determinant in colorectal cancer (CRC). Here the authors show that tumor infiltrating neutrophils expressing high levels of CD15 interact with CD8+ T effector memory skewing them to produce GZMK, associated with tumor progression in CRC patients.

In this study, we investigated the effects of solid lipid nanoparticle (SLN) nanocrystallization on the stability of two fractions of oat globulin-derived peptides. i.e., OGL, with molecular weight (MW)

This study clarified the effects of well-characterized oat globulin peptides on antidiabetic drug targets (dipeptidyl peptidase IV [DPP4], α-glucosidase, glucose transporters 2 and 5 [GLUT2, GLUT5]) in Caco-2 cells. Twenty-two peptides with over 8 residues were identified from the tryptic hydrolysates (OGb, MM